mirror of
https://github.com/esphome/esphome-docs.git
synced 2024-11-05 09:20:08 +01:00
b9c710a133
Co-authored-by: Jesse Hills <3060199+jesserockz@users.noreply.github.com>
150 lines
5.8 KiB
ReStructuredText
150 lines
5.8 KiB
ReStructuredText
Binary Sensor Map
|
|
=================
|
|
|
|
.. seo::
|
|
:description: Instructions for setting up a Binary Sensor Map
|
|
:image: binary_sensor_map.jpg
|
|
|
|
The ``binary_sensor_map`` sensor platform allows you to map multiple :doc:`binary sensor </components/binary_sensor/index>`
|
|
to an individual value. Depending on the state of each binary sensor, its associated configured parameters, and this sensor's mapping type,
|
|
the ``binary_sensor_map`` publishes a single numerical value.
|
|
|
|
Use this sensor to combine one or more binary sensors' ``ON`` or ``OFF`` states into a numerical value. Some possible use cases include
|
|
touch devices and determining Bayesian probabilities for an event.
|
|
|
|
This platform supports three measurement types: ``BAYESIAN``, ``GROUP``, and ``SUM``.
|
|
You need to specify your desired mapping with the ``type:`` configuration value.
|
|
|
|
When using the ``BAYESIAN`` type, add your binary sensors as ``observations`` to the binary sensor map.
|
|
If you use the ``GROUP`` or ``SUM`` type, add your binary sensors as ``channels``.
|
|
The maximum amount of observations/channels supported is 64.
|
|
|
|
- ``BAYESIAN`` This type replicates Home Assistant's `Bayesian sensor <https://www.home-assistant.io/integrations/bayesian/>`__. Based on the observation states, this sensor returns the Bayesian probability of a particular event occurring. The configured ``prior:`` probability is the likelihood that the Bayesian event is true, ignoring all external influences. Every observation has its own ``prob_given_true`` and ``prob_given_false`` parameters. The ``prob_given_true:`` value is the probability that the observation's binary sensor is ``ON`` when the Bayesian event is ``true``. The ``prob_given_false:`` value is the probability that the observation's binary sensor is ``ON`` when the Bayesian event is ``false``. Use an :doc:`/components/binary_sensor/analog_threshold` to convert this sensor's probability to a binary ``ON`` or ``OFF`` by setting an appropriate threshold.
|
|
|
|
.. code-block:: yaml
|
|
|
|
# Example configuration entry
|
|
sensor:
|
|
- platform: binary_sensor_map
|
|
id: bayesian_prob
|
|
name: 'Bayesian Event Probability'
|
|
type: bayesian
|
|
prior: 0.4
|
|
observations:
|
|
- binary_sensor: binary_sensor_0
|
|
prob_given_true: 0.9
|
|
prob_given_false: 0.2
|
|
- binary_sensor: binary_sensor_1
|
|
prob_given_true: 0.6
|
|
prob_given_false: 0.1
|
|
|
|
binary_sensor:
|
|
# If the Bayesian probability is greater than 0.6,
|
|
# then predict the event is occuring
|
|
- platform: analog_threshold
|
|
name: "Bayesian Event Predicted State"
|
|
sensor_id: bayesian_prob
|
|
threshold: 0.6
|
|
# ...
|
|
|
|
- ``GROUP`` Each channel has its own ``value``. The sensor publishes the average value of all active
|
|
binary sensors or ``NAN`` if no sensors are active.
|
|
|
|
.. code-block:: yaml
|
|
|
|
# Example configuration entry
|
|
sensor:
|
|
- platform: binary_sensor_map
|
|
id: group_0
|
|
name: 'Group Map 0'
|
|
type: GROUP
|
|
channels:
|
|
- binary_sensor: touchkey0
|
|
value: 0
|
|
- binary_sensor: touchkey1
|
|
value: 10
|
|
- binary_sensor: touchkey2
|
|
value: 20
|
|
- binary_sensor: touchkey3
|
|
value: 30
|
|
|
|
# Example binary sensors using MPR121 component
|
|
mpr121:
|
|
id: mpr121_first
|
|
address: 0x5A
|
|
|
|
binary_sensor:
|
|
- platform: mpr121
|
|
channel: 0
|
|
id: touchkey0
|
|
# ...
|
|
|
|
- ``SUM`` Each channel has its own ``value``. The sensor publishes the sum of all the active
|
|
binary sensors values or ``0`` if no sensors are active.
|
|
|
|
.. code-block:: yaml
|
|
|
|
# Example configuration entry
|
|
sensor:
|
|
- platform: binary_sensor_map
|
|
id: group_0
|
|
name: 'Group Map 0'
|
|
type: sum
|
|
channels:
|
|
- binary_sensor: bit0
|
|
value: 1
|
|
- binary_sensor: bit1
|
|
value: 2
|
|
- binary_sensor: bit2
|
|
value: 4
|
|
- binary_sensor: bit3
|
|
value: 8
|
|
|
|
binary_sensor:
|
|
- platform: gpio
|
|
pin: 4
|
|
id: bit0
|
|
|
|
- platform: gpio
|
|
pin: 5
|
|
id: bit1
|
|
|
|
- platform: gpio
|
|
pin: 6
|
|
id: bit2
|
|
|
|
- platform: gpio
|
|
pin: 7
|
|
id: bit3
|
|
# ...
|
|
|
|
Configuration variables:
|
|
------------------------
|
|
|
|
- **name** (**Required**, string): The name of the sensor.
|
|
- **type** (**Required**, string): The sensor type. Should be one of: ``BAYESIAN``, ``GROUP``, or ``SUM``.
|
|
- **channels** (**Required for GROUP or SUM types**): A list of channels that are mapped to certain values.
|
|
|
|
- **binary_sensor** (**Required**): The id of the :doc:`binary sensor </components/binary_sensor/index>`
|
|
to add as a channel for this sensor.
|
|
- **value** (**Required**): The value this channel should report when its binary sensor is active.
|
|
- **prior** (**Required for BAYESIAN type**, float between 0 and 1): The prior probability of the event.
|
|
- **observations** (**Required for BAYESIAN type**): A list of observations that influence the Bayesian probability of the event.
|
|
|
|
- **binary_sensor** (**Required**): The id of the :doc:`binary sensor </components/binary_sensor/index>`
|
|
to add as an observation.
|
|
- **prob_given_true** (**Required**, float between 0 and 1): Assuming the event is true, the probability this observation is on.
|
|
- **prob_given_false** (**Required**, float between 0 and 1): Assuming the event is false, the probability this observation is on.
|
|
|
|
- All other options from :ref:`Sensor <config-sensor>`.
|
|
|
|
See Also
|
|
--------
|
|
|
|
- :doc:`/components/binary_sensor/mpr121`
|
|
- :doc:`/components/binary_sensor/analog_threshold`
|
|
- :ref:`sensor-filters`
|
|
- :apiref:`binary_sensor_map/binary_sensor_map.h`
|
|
- `Bayesian sensor in Home Assistant <https://www.home-assistant.io/integrations/bayesian/>`__
|
|
- :ghedit:`Edit`
|